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Dynein Associates with oskar mRNPs and Is Required For Their Efficient Net Plus-End Localization in Drosophila Oocytes

Overview of attention for article published in PLOS ONE, November 2013
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Title
Dynein Associates with oskar mRNPs and Is Required For Their Efficient Net Plus-End Localization in Drosophila Oocytes
Published in
PLOS ONE, November 2013
DOI 10.1371/journal.pone.0080605
Pubmed ID
Authors

Paulomi Sanghavi, Shobha Laxani, Xuan Li, Simon L. Bullock, Graydon B. Gonsalvez

Abstract

In order for eukaryotic cells to function properly, they must establish polarity. The Drosophila oocyte uses mRNA localization to establish polarity and hence provides a genetically tractable model in which to study this process. The spatial restriction of oskar mRNA and its subsequent protein product is necessary for embryonic patterning. The localization of oskar mRNA requires microtubules and microtubule-based motor proteins. Null mutants in Kinesin heavy chain (Khc), the motor subunit of the plus end-directed Kinesin-1, result in oskar mRNA delocalization. Although the majority of oskar particles are non-motile in khc nulls, a small fraction of particles display active motility. Thus, a motor other than Kinesin-1 could conceivably also participate in oskar mRNA localization. Here we show that Dynein heavy chain (Dhc), the motor subunit of the minus end-directed Dynein complex, extensively co-localizes with Khc and oskar mRNA. In addition, immunoprecipitation of the Dynein complex specifically co-precipitated oskar mRNA and Khc. Lastly, germline-specific depletion of Dhc resulted in oskar mRNA and Khc delocalization. Our results therefore suggest that efficient posterior localization of oskar mRNA requires the concerted activities of both Dynein and Kinesin-1.

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Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
United States 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 29%
Researcher 8 23%
Professor > Associate Professor 4 11%
Student > Master 2 6%
Professor 2 6%
Other 3 9%
Unknown 6 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 51%
Biochemistry, Genetics and Molecular Biology 8 23%
Computer Science 1 3%
Engineering 1 3%
Unknown 7 20%